Policy-Oriented Tool for Energy and Climate Change Impact Assessment

POTEnCIA is a modelling tool for the EU energy system, covering all energy demand sectors (i.e. residential, services, industry, transport and agriculture) and energy supply. The model covers each EU Member State separately, while offering, in addition, the option of addressing the EU27 and UK energy system as a whole. Model outputs are provided in annual time steps for the time horizon 2000-2050. Historical data (2000-2015) are consistent with Eurostat and based on the JRC Integrated Database of the European Energy System (JRC-IDEES), which was developed in parallel to the POTEnCIA model and is publicly available. 

POTEnCIA follows a hybrid partial equilibrium approach. It combines behavioural decisions with (imperfect) optimisation, using detailed techno-economic data, therefore allowing for an analysis of both technology-oriented policies and of those addressing behavioural change. Special features and mechanisms are introduced in POTEnCIA as to appropriately represent the transformation of today’s energy systems and to assess a wide variety of potential energy related policies and measures.

The model can be used for ex-ante policy assessment or policy evaluation. It is designed to assess the impacts of alternative energy and climate policies on the energy system, under different hypotheses about the framework conditions within the energy markets. In addition, explicit policies can be directly addressed, such as those related to energy taxation, efficiency standards, feed-in-tariffs, etc. The main use of the tool is to perform comparative analysis of scenarios.

Scope

POTEnCIA is a modelling tool for the EU energy system that follows a hybrid partial equilibrium approach. It combines behavioural decisions with detailed techno-economic data. The tool therefore allows for an analysis of both technology-oriented policies and of those addressing behavioural change.

The model runs on an annual basis, based on historical time series and with a typical projection timeline to 2050. Historical time series are taken from the publicly available JRC Integrated Database of the European Energy System (JRC-IDEES), which is consistent to Eurostat energy balances and has been developed in parallel to the POTEnCIA model.

Each country is modelled separately as to appropriately capture the existing differences in energy system structures, levels of energy service, technology characteristics, resources availability etc. POTEnCIA can also run for the EU27 and UK as a whole as to assess cross-country interactions such as imports/exports or policies defined at EU level.

Structure and approach

In each year, POTEnCIA successively optimises demand and supply across energy carriers.

In order to meet the foreseen activity levels in a given year (e.g. tonnes of steel produced; mobility; indoor temperature) in each demand sector – i.e. residential, industry, services, transport and agriculture – a certain energy service is required. This energy service is met by optimising both the stock and use of the energy-consuming equipment under various constraints.

Methodologically, each demand and supply sector in POTEnCIA is formulated by means of a representative agent[1] that implicitly seeks to minimise its cost and/or to maximise its benefit (profit, utility, etc.) under constraints related to behavioural preferences, technology availability, level of activity desired, degree of comfort sought, equipment installed, fuel availability and environmental considerations. Discrete choice modelling is applied as concerns the energy actors' investment decision-making.

The behaviour of the representative agents within POTEnCIA is captured by causational equations (in many cases highly non-linear). Other non-linear relationships are introduced in the model as to represent the scarcity of resources, the level of exploitation of existing infrastructure and technology dynamics.

At the level of the overall energy system, in each year the model determines the equilibrium across the different sectors through prices, for all scarce resources (not only the traditional energy carriers, but also renewable energy, other efficiency and environmental –CO2 related- costs in relation to their potentials). In this process different agents act as price-takers, price makers or simultaneously both. This equilibrium is repeated in each year of the projection period, incorporating dynamic relationships reflecting previous decisions of economic agents from one year to the next. Given the complexity of the problem and taking advantage of the dynamic recursive annual time steps, POTEnCIA makes use of the equilibrium prices with a one year lag. Such lag also reflects observed delays with which price signals pass on to economic agents in the sector. 

For network-supplied forms of energy (electricity and derived heat), capacity planning and dispatch decisions are optimised to fulfil the hourly load of an entire year (i.e. 8760 hours) at the minimum cost. The hourly load is generally the aggregate of inflexible (computed by linking exogenously defined load profiles at the level of individual energy uses to the corresponding energy requirements identified on the demand-side simulation) and flexible (storage loading, demand response, etc.) elements.

Methodologically, modelling of power generation in POTEnCIA follows a non-linear optimisation approach, addressing capacity planning and power plant dispatching under:

• constraints on inflexible demand (synchronised chronological load curves for electricity, and distributed steam and heat demand) and flexible demand (e.g. limits on demand response);
• constraints related to the operational constraints of power generation and energy storage plants (including planned maintenance);
• fuel supply constraints (including chronological load curves for intermittent renewable energy forms, such as wind and solar energy);
• grid constraints (including exogenous net transfer capacities to limit the endogenous hourly electricity trading across countries, and the possibility to invest in additional transfer capacity); and
• policy constraints

A variety of sector-specific assumptions are applied within the model. These concern the different planning horizons, the formation of expectations about prices, technologies, resources, etc., and the role of those expectations in economic decision making. Expectations about future markets are also accounted for. 

The role of energy installations/equipment and vintages

The POTEnCIA model, though being an economic model of the entire energy system, deals with energy consumption at the level of a 'representative consumption unit'. Such representative consumption unit constitutes of, for example, an industrial installation needed to produce one unit of output; a household installation for thermal uses in the residential sector; a (representative) electrical appliance; a vehicle for private transport.

The investment choices made by the 'representative agent' therefore represent physical entities rather than investments in a certain continuous capacity. For example, a new household requires a space heating boiler of a certain size, a water heating equipment of another size and a certain number of appliances etc.  All of these installations have specific techno-economic characteristics.

The vintage equipment characteristics are explicitly considered over the entire modelling horizon both on the demand and supply side, allowing for an accurate representation of the features of the energy system at each point in time. As a consequence, POTEnCIA can provide consistent time series of different futures of the energy system, explicitly quantifying also the costs of stranded investment and early retirement.

[1] Within each sector, the representative economic agent summarises the individual choices of various decision makers under different conditions. This yields a 'representative' consumption profile in the sector in terms of energy related equipment in use, consumer preferences, etc.

• Historical data (JRC-IDEES)
• Demographic assumptions (Eurostat)
• Macroeconomic assumptions (DG ECFIN; GEM-E3)
• International fuel prices (POLES)